ADEC 7220 Linear Algebra and Vector Calculus

Machine learning is the design of algorithms that routinely learn and adapt with use to discover hidden properties, patterns, and trends in complex data. This is a semester course on foundational methods in linear algebra and vector calculus to understand the structure and dimensionality of large and complex datasets.

Course overview

Department
Advancing Studies
School
ADV
Credits
3
Level
Graduate
Offered
Periodically

Course evaluations

Response-weighted averages from Boston College’s official course evaluations (Avalanche/Blue).

Course rating
4.39 / 5 · Very Good
31 responses
Instructor rating
4.77 / 5 · Excellent
31 responses
Terms evaluated
9
Most recent: Spring 2026

Scales: overall ratings run from 1 (poor) to 5 (excellent); agreement questions from 1 (strongly disagree) to 5 (strongly agree); weekly effort from 1 (up to 1 hour) to 5 (10 or more hours).

Evaluations by term and instructor
TermInstructorCourse overallInstructor overallWell organizedClear learning objectivesIntellectually challengingHelpful assignmentsApplicable beyond courseAttendance necessaryWeekly effortResponses
Spring 2026Leslie Servi—————————1 of 1
Spring 2026Lorin Gerraughty—————————1 of 1
Fall 2025Arvind Sharma5.05.05.05.04.34.84.84.84–6 hrs/week4 of 5
Fall 2025 (midterm)Lorin Gerraughty3.05.04.03.05.04.03.0—10+ hrs/week1 of 3
Summer 2025Lorin Gerraughty4.35.05.04.84.54.74.74.44–6 hrs/week6 of 7
Spring 2025Arvind Sharma4.34.84.54.84.54.54.54.34–6 hrs/week4 of 5
Fall 2024Lorin Gerraughty4.75.05.05.05.04.74.34.07–9 hrs/week3 of 6
Spring 2024Arvind Sharma4.55.04.54.54.54.54.54.0—2 of 4
Fall 2023Paul Garvey—————————3 of 4
Fall 2023 (midterm)Lorin Gerraughty4.04.05.05.04.05.05.05.04–6 hrs/week1 of 3
Spring 2023Lorin Gerraughty5.05.05.05.05.05.05.05.0—2 of 3
Fall 2022Lorin Gerraughty4.04.53.54.05.04.03.03.0—2 of 2
Fall 2022Paul Garvey5.05.05.05.05.05.05.05.07–9 hrs/week1 of 3

Data freshness

Course and evaluation data last updated 2026-10-09. Source details and limitations are documented in Data Sources and Methodology.

Instructors

  • Arvind Sharma
    Fall 2025, Spring 2025, Spring 2024 · Official rating 4.90/5
  • Leslie Servi
    Spring 2026 · Official rating 5.00/5
  • Lorin Gerraughty
    Spring 2026, Summer 2025, Midterm Fall 2025, Spring 2023, Midterm Fall 2023, Fall 2022, 2024FALL1 · Official rating 4.62/5
  • Paul Garvey
    Fall 2023, Fall 2022 · Official rating 5.00/5